How Billions of TrivialDataPoints can Lead to UnderstandingPeter Norvig (Director of Research, Google) presents as part of the UBC Department of Computer Science's Distinguished Lecture Series, September 23, 2010.
In decades past, models of human language were wrought from the sweat and pencils of linguists. In the modern day, it is more common to think of language modeling as an exercise in probabilistic inference from data: we observe how words and combinations of words are used, and from that build computer models of what the phrases mean. This approach is hopeless with a small amount of data, but somewhere in the range of millions or billions of examples, we pass a threshold, and the hopeless suddenly becomes effective, and computer models sometimes meet or exceed human performance. This talk gives examples of the data available in large repositories of text, images, and videos, and shows some tasks that can be accomplished with the resulting models.

published:11 Oct 2011

views:53725

The key to progressing from a novice programmer to an expert is mindful practice. In this class you will practice going from a problem description to a solution, using a series of assignments. With each problem you will learn new concepts, patterns, and methods that will expand your ability and help move you along the path from novice towards expertise.
http://www.udacity.com/overview/Course/cs212

published:28 Mar 2012

views:6521

"One of our challenges for the future is to describe to our markets and to our high-tech products what is it that we really want. In AI, there's a common goal of maximizing expected utility. We've spent decades on the 'expected' and the 'maximizing' parts, but have taken the 'utility' as a given. Until the public has the power to say what it is it really wants, the markets will choose poorly." - Peter Norvig, Director of Research, Google (2016)
Playlist: https://goo.gl/Xpxp5m
Long-form: https://goo.gl/tJT2ML
If you enjoyed this video, please subscribe and connect with me:
LinkedIn: https://www.linkedin.com/in/lexfridman
Twitter: https://twitter.com/lexfridman
Facebook: https://www.facebook.com/lexfridman
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Web: https://lex.mit.edu

published:30 Mar 2018

views:3637

Bringing together thought leaders in large-scale data analysis and technology to transform the way we diagnose, treat and prevent disease. Visit our website at http://bigdata.stanford.edu/.

published:14 Jun 2015

views:3572

May 23, 2016 Peter Norvig, Director of Research for Google, on developing state-of-the-art AI solutions for building tomorrow's intelligent systems.
May 23, 2016 Peter Norvig, Director of Research for Google, on developing state-of-the-art AI solutions for building tomorrow's intelligent systems. Silicon Valley .

published:28 Oct 2016

views:3080

Information and subscription on http://www.usievents.com
Director of Research at Google Inc., Peter Norvig is a reference in terms of Machine Learning. He’s always looking at the world to re-build it, playing with programs and applications that nowadays have a dominant role in our world. “The world is made of lines” and we can draw anything with it, manually or numerically.
Peter Norvig’s talk is about Deploying machine learning applications in the Enterprise.
More companies are taking advantage of the opportunity to harness large amounts of data to make more accurate predictions, and sometimes to invent entire new classes of applications that couldn't be done before. In this talk, Peter Norvig uses the exemple of Google’s photo reconnaissance or its Automatic spell-checker. “21 lines of code can now be enough to build a whole program which self-feeds”.
But like any engineering discipline, machine learning brings with it some potential pitfalls that practitioners must learn to avoid.
FollowUSI on Twitter: https://twitter.com/USIEvents
Follow USI on LinkedIn: http://linkd.in/13Ls21Y
Subscribe to our channel: http://bit.ly/19sPpSp

Peter

Peter often is used to refer to Saint Peter, a disciple of Jesus Christ. It can also refer to many other people, of which only a few are listed here. This page only lists people commonly referred to as "Peter" and nothing else; for others, please see List of people named Peter.

Artificial intelligence

Artificial intelligence (AI) is the intelligence exhibited by machines or software. It is also the name of the academic field of study which studies how to create computers and computer software that are capable of intelligent behavior. Major AI researchers and textbooks define this field as "the study and design of intelligent agents", in which an intelligent agent is a system that perceives its environment and takes actions that maximize its chances of success.John McCarthy, who coined the term in 1955, defines it as "the science and engineering of making intelligent machines".

AI research is highly technical and specialized, and is deeply divided into subfields that often fail to communicate with each other. Some of the division is due to social and cultural factors: subfields have grown up around particular institutions and the work of individual researchers. AI research is also divided by several technical issues. Some subfields focus on the solution of specific problems. Others focus on one of several possible approaches or on the use of a particular tool or towards the accomplishment of particular applications.

Deep learning

Deep learning (deep structured learning, hierarchical learning or deep machine learning) is a branch of machine learning based on a set of algorithms that attempt to model high-level abstractions in data by using multiple processing layers with complex structures, or otherwise composed of multiple non-linear transformations.

Deep learning is part of a broader family of machine learning methods based on learning representations of data. An observation (e.g., an image) can be represented in many ways such as a vector of intensity values per pixel, or in a more abstract way as a set of edges, regions of particular shape, etc. Some representations make it easier to learn tasks (e.g., face recognition or facial expression recognition) from examples. One of the promises of deep learning is replacing handcrafted features with efficient algorithms for unsupervised or semi-supervisedfeature learning and hierarchical feature extraction.

Research in this area attempts to make better representations and create models to learn these representations from large-scale unlabeled data. Some of the representations are inspired by advances in neuroscience and are loosely based on interpretation of information processing and communication patterns in a nervous system, such as neural coding which attempts to define a relationship between various stimuli and associated neuronal responses in the brain.

Peter Norvig - The Unreasonable Effectiveness of Data

How Billions of TrivialDataPoints can Lead to UnderstandingPeter Norvig (Director of Research, Google) presents as part of the UBC Department of Computer Science's Distinguished Lecture Series, September 23, 2010.
In decades past, models of human language were wrought from the sweat and pencils of linguists. In the modern day, it is more common to think of language modeling as an exercise in probabilistic inference from data: we observe how words and combinations of words are used, and from that build computer models of what the phrases mean. This approach is hopeless with a small amount of data, but somewhere in the range of millions or billions of examples, we pass a threshold, and the hopeless suddenly becomes effective, and computer models sometimes meet or exceed human performance. This talk gives examples of the data available in large repositories of text, images, and videos, and shows some tasks that can be accomplished with the resulting models.

1:36

Learn to Design Computer Programs with Peter Norvig!

Learn to Design Computer Programs with Peter Norvig!

Learn to Design Computer Programs with Peter Norvig!

The key to progressing from a novice programmer to an expert is mindful practice. In this class you will practice going from a problem description to a solution, using a series of assignments. With each problem you will learn new concepts, patterns, and methods that will expand your ability and help move you along the path from novice towards expertise.
http://www.udacity.com/overview/Course/cs212

2:29

Peter Norvig: Utility in AI

Peter Norvig: Utility in AI

Peter Norvig: Utility in AI

"One of our challenges for the future is to describe to our markets and to our high-tech products what is it that we really want. In AI, there's a common goal of maximizing expected utility. We've spent decades on the 'expected' and the 'maximizing' parts, but have taken the 'utility' as a given. Until the public has the power to say what it is it really wants, the markets will choose poorly." - Peter Norvig, Director of Research, Google (2016)
Playlist: https://goo.gl/Xpxp5m
Long-form: https://goo.gl/tJT2ML
If you enjoyed this video, please subscribe and connect with me:
LinkedIn: https://www.linkedin.com/in/lexfridman
Twitter: https://twitter.com/lexfridman
Facebook: https://www.facebook.com/lexfridman
Instagram: https://www.instagram.com/lexfridman
Web: https://lex.mit.edu

14:46

Peter Norvig, Google - Stanford Big Data 2015

Peter Norvig, Google - Stanford Big Data 2015

Peter Norvig, Google - Stanford Big Data 2015

Bringing together thought leaders in large-scale data analysis and technology to transform the way we diagnose, treat and prevent disease. Visit our website at http://bigdata.stanford.edu/.

29:32

Google's Peter Norvig State of the Art AI: Building Tomorrow’s Intelligent Systems

Google's Peter Norvig State of the Art AI: Building Tomorrow’s Intelligent Systems

Google's Peter Norvig State of the Art AI: Building Tomorrow’s Intelligent Systems

May 23, 2016 Peter Norvig, Director of Research for Google, on developing state-of-the-art AI solutions for building tomorrow's intelligent systems.
May 23, 2016 Peter Norvig, Director of Research for Google, on developing state-of-the-art AI solutions for building tomorrow's intelligent systems. Silicon Valley .

Information and subscription on http://www.usievents.com
Director of Research at Google Inc., Peter Norvig is a reference in terms of Machine Learning. He’s always looking at the world to re-build it, playing with programs and applications that nowadays have a dominant role in our world. “The world is made of lines” and we can draw anything with it, manually or numerically.
Peter Norvig’s talk is about Deploying machine learning applications in the Enterprise.
More companies are taking advantage of the opportunity to harness large amounts of data to make more accurate predictions, and sometimes to invent entire new classes of applications that couldn't be done before. In this talk, Peter Norvig uses the exemple of Google’s photo reconnaissance or its Automatic spell-checker. “21 lines of code can now be enough to build a whole program which self-feeds”.
But like any engineering discipline, machine learning brings with it some potential pitfalls that practitioners must learn to avoid.
FollowUSI on Twitter: https://twitter.com/USIEvents
Follow USI on LinkedIn: http://linkd.in/13Ls21Y
Subscribe to our channel: http://bit.ly/19sPpSp

7:43

You Can Always Get What You Want — But Not What You Need (Graduation 2016)

You Can Always Get What You Want — But Not What You Need (Graduation 2016)

You Can Always Get What You Want — But Not What You Need (Graduation 2016)

Peter Norvig - Deep Learning and Artificial Intelligence Symposium

May 1, 2017 - In less than a decade, the field of “artificial intelligence” or “AI” has been jolted by the extraordinary and unexpected success of a set of techniques now called “Deep Learning”. These methods (with some other related rapidly advancing technologies) already exceed average human performance in some kinds of image understanding; spoken word recognition and language translation; and indeed some tasks, like the game of Go, previously thought to require generalized human intelligence. AI may soon replace humans in driving cars, coding new software, robotic caregiving, and making healthcare decisions. The societal implications are enormous.
Peter Norvig, Director of Research, Google Inc. presents "Rethinking the Software Industry"

Artificial intelligence is playing an increasingly important role in new software products, but the workflow of an AI researcher is quite different from the workflow of the software developer. Peter Norvig explains how the two can come together.
Subscribe to O'Reilly on YouTube: http://goo.gl/n3QSYi
Follow O'Reilly on
Twitter: http://twitter.com/oreillymedia
Facebook: http://facebook.com/OReilly
Google: http://plus.google.com/+oreillymedia

11:43

AI and open source paired to transform and disrupt with Peter Norvig (Google)

AI and open source paired to transform and disrupt with Peter Norvig (Google)

AI and open source paired to transform and disrupt with Peter Norvig (Google)

Peter Norvig - The Unreasonable Effectiveness of Data

How Billions of TrivialDataPoints can Lead to UnderstandingPeter Norvig (Director of Research, Google) presents as part of the UBC Department of Computer Science's Distinguished Lecture Series, September 23, 2010.
In decades past, models of human language were wrought from the sweat and pencils of linguists. In the modern day, it is more common to think of language modeling as an exercise in probabilistic inference from data: we observe how words and combinations of words are used, and from that build computer models of what the phrases mean. This approach is hopeless with a small amount of data, but somewhere in the range of millions or billions of examples, we pass a threshold, and the hopeless suddenly becomes effective, and computer models sometimes meet or exceed human perfor...

published: 11 Oct 2011

Learn to Design Computer Programs with Peter Norvig!

The key to progressing from a novice programmer to an expert is mindful practice. In this class you will practice going from a problem description to a solution, using a series of assignments. With each problem you will learn new concepts, patterns, and methods that will expand your ability and help move you along the path from novice towards expertise.
http://www.udacity.com/overview/Course/cs212

published: 28 Mar 2012

Peter Norvig: Utility in AI

"One of our challenges for the future is to describe to our markets and to our high-tech products what is it that we really want. In AI, there's a common goal of maximizing expected utility. We've spent decades on the 'expected' and the 'maximizing' parts, but have taken the 'utility' as a given. Until the public has the power to say what it is it really wants, the markets will choose poorly." - Peter Norvig, Director of Research, Google (2016)
Playlist: https://goo.gl/Xpxp5m
Long-form: https://goo.gl/tJT2ML
If you enjoyed this video, please subscribe and connect with me:
LinkedIn: https://www.linkedin.com/in/lexfridman
Twitter: https://twitter.com/lexfridman
Facebook: https://www.facebook.com/lexfridman
Instagram: https://www.instagram.com/lexfridman
Web: https://lex.mit.edu

published: 30 Mar 2018

Peter Norvig, Google - Stanford Big Data 2015

Bringing together thought leaders in large-scale data analysis and technology to transform the way we diagnose, treat and prevent disease. Visit our website at http://bigdata.stanford.edu/.

published: 14 Jun 2015

Google's Peter Norvig State of the Art AI: Building Tomorrow’s Intelligent Systems

May 23, 2016 Peter Norvig, Director of Research for Google, on developing state-of-the-art AI solutions for building tomorrow's intelligent systems.
May 23, 2016 Peter Norvig, Director of Research for Google, on developing state-of-the-art AI solutions for building tomorrow's intelligent systems. Silicon Valley .

Information and subscription on http://www.usievents.com
Director of Research at Google Inc., Peter Norvig is a reference in terms of Machine Learning. He’s always looking at the world to re-build it, playing with programs and applications that nowadays have a dominant role in our world. “The world is made of lines” and we can draw anything with it, manually or numerically.
Peter Norvig’s talk is about Deploying machine learning applications in the Enterprise.
More companies are taking advantage of the opportunity to harness large amounts of data to make more accurate predictions, and sometimes to invent entire new classes of applications that couldn't be done before. In this talk, Peter Norvig uses the exemple of Google’s photo reconnaissance or its Automatic spell-checker. “21 lines o...

published: 09 Jul 2015

You Can Always Get What You Want — But Not What You Need (Graduation 2016)

Peter Norvig - Deep Learning and Artificial Intelligence Symposium

May 1, 2017 - In less than a decade, the field of “artificial intelligence” or “AI” has been jolted by the extraordinary and unexpected success of a set of techniques now called “Deep Learning”. These methods (with some other related rapidly advancing technologies) already exceed average human performance in some kinds of image understanding; spoken word recognition and language translation; and indeed some tasks, like the game of Go, previously thought to require generalized human intelligence. AI may soon replace humans in driving cars, coding new software, robotic caregiving, and making healthcare decisions. The societal implications are enormous.
Peter Norvig, Director of Research, Google Inc. presents "Rethinking the Software Industry"

Artificial intelligence is playing an increasingly important role in new software products, but the workflow of an AI researcher is quite different from the workflow of the software developer. Peter Norvig explains how the two can come together.
Subscribe to O'Reilly on YouTube: http://goo.gl/n3QSYi
Follow O'Reilly on
Twitter: http://twitter.com/oreillymedia
Facebook: http://facebook.com/OReilly
Google: http://plus.google.com/+oreillymedia

published: 17 Jul 2017

AI and open source paired to transform and disrupt with Peter Norvig (Google)

Peter Norvig | The Science and Engineering of Online Learning

Peter Norvig, Director of Research at Google, talks about how we have known that learning works best with a one-on-one tutor who encourages the student to keep working until mastery is achieved. We can't afford, or find, enough excellent human tutors, so the question is whether there are technologies that are ready to handle the job, and whether anything is different now than in decades past. We will review the state of the art in online teaching, and where the practice may be heading.
Peter Norvig was the head of the Computational Sciences Division at NASA Ames Research Center, making him NASA's senior computer scientist. He received the NASA Exceptional Achievement Award in 2001. He has served as an assistant professor at the University of Southern California and a research faculty memb...

How Billions of TrivialDataPoints can Lead to UnderstandingPeter Norvig (Director of Research, Google) presents as part of the UBC Department of Computer Science's Distinguished Lecture Series, September 23, 2010.
In decades past, models of human language were wrought from the sweat and pencils of linguists. In the modern day, it is more common to think of language modeling as an exercise in probabilistic inference from data: we observe how words and combinations of words are used, and from that build computer models of what the phrases mean. This approach is hopeless with a small amount of data, but somewhere in the range of millions or billions of examples, we pass a threshold, and the hopeless suddenly becomes effective, and computer models sometimes meet or exceed human performance. This talk gives examples of the data available in large repositories of text, images, and videos, and shows some tasks that can be accomplished with the resulting models.

How Billions of TrivialDataPoints can Lead to UnderstandingPeter Norvig (Director of Research, Google) presents as part of the UBC Department of Computer Science's Distinguished Lecture Series, September 23, 2010.
In decades past, models of human language were wrought from the sweat and pencils of linguists. In the modern day, it is more common to think of language modeling as an exercise in probabilistic inference from data: we observe how words and combinations of words are used, and from that build computer models of what the phrases mean. This approach is hopeless with a small amount of data, but somewhere in the range of millions or billions of examples, we pass a threshold, and the hopeless suddenly becomes effective, and computer models sometimes meet or exceed human performance. This talk gives examples of the data available in large repositories of text, images, and videos, and shows some tasks that can be accomplished with the resulting models.

Learn to Design Computer Programs with Peter Norvig!

The key to progressing from a novice programmer to an expert is mindful practice. In this class you will practice going from a problem description to a solution...

The key to progressing from a novice programmer to an expert is mindful practice. In this class you will practice going from a problem description to a solution, using a series of assignments. With each problem you will learn new concepts, patterns, and methods that will expand your ability and help move you along the path from novice towards expertise.
http://www.udacity.com/overview/Course/cs212

The key to progressing from a novice programmer to an expert is mindful practice. In this class you will practice going from a problem description to a solution, using a series of assignments. With each problem you will learn new concepts, patterns, and methods that will expand your ability and help move you along the path from novice towards expertise.
http://www.udacity.com/overview/Course/cs212

Peter Norvig: Utility in AI

"One of our challenges for the future is to describe to our markets and to our high-tech products what is it that we really want. In AI, there's a common goal o...

"One of our challenges for the future is to describe to our markets and to our high-tech products what is it that we really want. In AI, there's a common goal of maximizing expected utility. We've spent decades on the 'expected' and the 'maximizing' parts, but have taken the 'utility' as a given. Until the public has the power to say what it is it really wants, the markets will choose poorly." - Peter Norvig, Director of Research, Google (2016)
Playlist: https://goo.gl/Xpxp5m
Long-form: https://goo.gl/tJT2ML
If you enjoyed this video, please subscribe and connect with me:
LinkedIn: https://www.linkedin.com/in/lexfridman
Twitter: https://twitter.com/lexfridman
Facebook: https://www.facebook.com/lexfridman
Instagram: https://www.instagram.com/lexfridman
Web: https://lex.mit.edu

"One of our challenges for the future is to describe to our markets and to our high-tech products what is it that we really want. In AI, there's a common goal of maximizing expected utility. We've spent decades on the 'expected' and the 'maximizing' parts, but have taken the 'utility' as a given. Until the public has the power to say what it is it really wants, the markets will choose poorly." - Peter Norvig, Director of Research, Google (2016)
Playlist: https://goo.gl/Xpxp5m
Long-form: https://goo.gl/tJT2ML
If you enjoyed this video, please subscribe and connect with me:
LinkedIn: https://www.linkedin.com/in/lexfridman
Twitter: https://twitter.com/lexfridman
Facebook: https://www.facebook.com/lexfridman
Instagram: https://www.instagram.com/lexfridman
Web: https://lex.mit.edu

May 23, 2016 Peter Norvig, Director of Research for Google, on developing state-of-the-art AI solutions for building tomorrow's intelligent systems.
May 23, 2016 Peter Norvig, Director of Research for Google, on developing state-of-the-art AI solutions for building tomorrow's intelligent systems. Silicon Valley .

May 23, 2016 Peter Norvig, Director of Research for Google, on developing state-of-the-art AI solutions for building tomorrow's intelligent systems.
May 23, 2016 Peter Norvig, Director of Research for Google, on developing state-of-the-art AI solutions for building tomorrow's intelligent systems. Silicon Valley .

Information and subscription on http://www.usievents.com
Director of Research at Google Inc., Peter Norvig is a reference in terms of Machine Learning. He’s always looking at the world to re-build it, playing with programs and applications that nowadays have a dominant role in our world. “The world is made of lines” and we can draw anything with it, manually or numerically.
Peter Norvig’s talk is about Deploying machine learning applications in the Enterprise.
More companies are taking advantage of the opportunity to harness large amounts of data to make more accurate predictions, and sometimes to invent entire new classes of applications that couldn't be done before. In this talk, Peter Norvig uses the exemple of Google’s photo reconnaissance or its Automatic spell-checker. “21 lines of code can now be enough to build a whole program which self-feeds”.
But like any engineering discipline, machine learning brings with it some potential pitfalls that practitioners must learn to avoid.
FollowUSI on Twitter: https://twitter.com/USIEvents
Follow USI on LinkedIn: http://linkd.in/13Ls21Y
Subscribe to our channel: http://bit.ly/19sPpSp

Information and subscription on http://www.usievents.com
Director of Research at Google Inc., Peter Norvig is a reference in terms of Machine Learning. He’s always looking at the world to re-build it, playing with programs and applications that nowadays have a dominant role in our world. “The world is made of lines” and we can draw anything with it, manually or numerically.
Peter Norvig’s talk is about Deploying machine learning applications in the Enterprise.
More companies are taking advantage of the opportunity to harness large amounts of data to make more accurate predictions, and sometimes to invent entire new classes of applications that couldn't be done before. In this talk, Peter Norvig uses the exemple of Google’s photo reconnaissance or its Automatic spell-checker. “21 lines of code can now be enough to build a whole program which self-feeds”.
But like any engineering discipline, machine learning brings with it some potential pitfalls that practitioners must learn to avoid.
FollowUSI on Twitter: https://twitter.com/USIEvents
Follow USI on LinkedIn: http://linkd.in/13Ls21Y
Subscribe to our channel: http://bit.ly/19sPpSp

Peter Norvig - Deep Learning and Artificial Intelligence Symposium

May 1, 2017 - In less than a decade, the field of “artificial intelligence” or “AI” has been jolted by the extraordinary and unexpected success of a set of tech...

May 1, 2017 - In less than a decade, the field of “artificial intelligence” or “AI” has been jolted by the extraordinary and unexpected success of a set of techniques now called “Deep Learning”. These methods (with some other related rapidly advancing technologies) already exceed average human performance in some kinds of image understanding; spoken word recognition and language translation; and indeed some tasks, like the game of Go, previously thought to require generalized human intelligence. AI may soon replace humans in driving cars, coding new software, robotic caregiving, and making healthcare decisions. The societal implications are enormous.
Peter Norvig, Director of Research, Google Inc. presents "Rethinking the Software Industry"

May 1, 2017 - In less than a decade, the field of “artificial intelligence” or “AI” has been jolted by the extraordinary and unexpected success of a set of techniques now called “Deep Learning”. These methods (with some other related rapidly advancing technologies) already exceed average human performance in some kinds of image understanding; spoken word recognition and language translation; and indeed some tasks, like the game of Go, previously thought to require generalized human intelligence. AI may soon replace humans in driving cars, coding new software, robotic caregiving, and making healthcare decisions. The societal implications are enormous.
Peter Norvig, Director of Research, Google Inc. presents "Rethinking the Software Industry"

Artificial intelligence is playing an increasingly important role in new software products, but the workflow of an AI researcher is quite different from the wor...

Artificial intelligence is playing an increasingly important role in new software products, but the workflow of an AI researcher is quite different from the workflow of the software developer. Peter Norvig explains how the two can come together.
Subscribe to O'Reilly on YouTube: http://goo.gl/n3QSYi
Follow O'Reilly on
Twitter: http://twitter.com/oreillymedia
Facebook: http://facebook.com/OReilly
Google: http://plus.google.com/+oreillymedia

Artificial intelligence is playing an increasingly important role in new software products, but the workflow of an AI researcher is quite different from the workflow of the software developer. Peter Norvig explains how the two can come together.
Subscribe to O'Reilly on YouTube: http://goo.gl/n3QSYi
Follow O'Reilly on
Twitter: http://twitter.com/oreillymedia
Facebook: http://facebook.com/OReilly
Google: http://plus.google.com/+oreillymedia

Peter Norvig | The Science and Engineering of Online Learning

Peter Norvig, Director of Research at Google, talks about how we have known that learning works best with a one-on-one tutor who encourages the student to keep working until mastery is achieved. We can't afford, or find, enough excellent human tutors, so the question is whether there are technologies that are ready to handle the job, and whether anything is different now than in decades past. We will review the state of the art in online teaching, and where the practice may be heading.
Peter Norvig was the head of the Computational Sciences Division at NASA Ames Research Center, making him NASA's senior computer scientist. He received the NASA Exceptional Achievement Award in 2001. He has served as an assistant professor at the University of Southern California and a research faculty memb...

Guido Van Rossum - Design of Computer Programs

Peter Norvig Q&A

published: 15 Mar 2014

Geoffrey Hinton: The Godfather of Deep Learning

When Geoffrey Hinton, a researcher at Google and professor emeritus at the University of Toronto, began his work in deep learning in the 1970s, he was told he would spend his life toiling away in obscurity. Deep learning is a form of artificial intelligence that mimics the human brain. Now, four decades later, his research is revolutionizing AI. He joins The Agenda to discuss his work and what kept him going.

published: 15 Mar 2016

Interview with Danish hooligan (Denmark-Sweden)

A nine minutes long interview in Danish with the hooligan that ran onto the lane and hit the referee in the 89th minute of the EURO Qualifier game between Denmark and Sweden the 2nd of June 2007.

Launchpad Studio with Malika Cantor and Peter Norvig: GCPPodcast 108

Original post: https://www.gcppodcast.com/post/episode-108-lauchpad-studio-with-malika-cantor-and-peter-norvig/
LaunchpadStudio, a product development acceleration program focused on helping machine learning startups iterate quickly, fail fast, and collaborate on best practices. Malika Cantor and Peter Norvig talk with Mark and Melanie this week about how the Launchpad Studio program is helping startups overcome data, expertise and tooling barriers by providing access to talent and resources and building universal best practices.

When Geoffrey Hinton, a researcher at Google and professor emeritus at the University of Toronto, began his work in deep learning in the 1970s, he was told he would spend his life toiling away in obscurity. Deep learning is a form of artificial intelligence that mimics the human brain. Now, four decades later, his research is revolutionizing AI. He joins The Agenda to discuss his work and what kept him going.

When Geoffrey Hinton, a researcher at Google and professor emeritus at the University of Toronto, began his work in deep learning in the 1970s, he was told he would spend his life toiling away in obscurity. Deep learning is a form of artificial intelligence that mimics the human brain. Now, four decades later, his research is revolutionizing AI. He joins The Agenda to discuss his work and what kept him going.

Launchpad Studio with Malika Cantor and Peter Norvig: GCPPodcast 108

Original post: https://www.gcppodcast.com/post/episode-108-lauchpad-studio-with-malika-cantor-and-peter-norvig/
LaunchpadStudio, a product development acceler...

Original post: https://www.gcppodcast.com/post/episode-108-lauchpad-studio-with-malika-cantor-and-peter-norvig/
LaunchpadStudio, a product development acceleration program focused on helping machine learning startups iterate quickly, fail fast, and collaborate on best practices. Malika Cantor and Peter Norvig talk with Mark and Melanie this week about how the Launchpad Studio program is helping startups overcome data, expertise and tooling barriers by providing access to talent and resources and building universal best practices.

Original post: https://www.gcppodcast.com/post/episode-108-lauchpad-studio-with-malika-cantor-and-peter-norvig/
LaunchpadStudio, a product development acceleration program focused on helping machine learning startups iterate quickly, fail fast, and collaborate on best practices. Malika Cantor and Peter Norvig talk with Mark and Melanie this week about how the Launchpad Studio program is helping startups overcome data, expertise and tooling barriers by providing access to talent and resources and building universal best practices.

[Recorded: November 5, 2011]
Join leading researchers Dr. Eric Horvitz of Microsoft Research and Dr. PeterNorvig of Google for an intriguing discussion about the past, present, and future of artificial intelligence, moderated by KQED's Tim Olson. We are extremely fortunate to have Eric and Peter on our stage -- they've known each other for several years, and can discuss everything from machine learning to data-driven science, the world of perception, speech recognition, robotics, self-driving cars, and even a computer called Watson. A WonderDialog indeed!
We are proud to partner with the Bay Area Science Festival on this Wonder Dialog. This event is also part of the Museum's Revolutionaries 2011 lecture series, featuring conversations with some of the most distinguished thinkers in the technology industry.

[Recorded: November 5, 2011]
Join leading researchers Dr. Eric Horvitz of Microsoft Research and Dr. PeterNorvig of Google for an intriguing discussion about the past, present, and future of artificial intelligence, moderated by KQED's Tim Olson. We are extremely fortunate to have Eric and Peter on our stage -- they've known each other for several years, and can discuss everything from machine learning to data-driven science, the world of perception, speech recognition, robotics, self-driving cars, and even a computer called Watson. A WonderDialog indeed!
We are proud to partner with the Bay Area Science Festival on this Wonder Dialog. This event is also part of the Museum's Revolutionaries 2011 lecture series, featuring conversations with some of the most distinguished thinkers in the technology industry.

Peter Norvig - The Unreasonable Effectiveness of Data

How Billions of TrivialDataPoints can Lead to UnderstandingPeter Norvig (Director of Research, Google) presents as part of the UBC Department of Computer Science's Distinguished Lecture Series, September 23, 2010.
In decades past, models of human language were wrought from the sweat and pencils of linguists. In the modern day, it is more common to think of language modeling as an exercise in probabilistic inference from data: we observe how words and combinations of words are used, and from that build computer models of what the phrases mean. This approach is hopeless with a small amount of data, but somewhere in the range of millions or billions of examples, we pass a threshold, and the hopeless suddenly becomes effective, and computer models sometimes meet or exceed human performance. This talk gives examples of the data available in large repositories of text, images, and videos, and shows some tasks that can be accomplished with the resulting models.

1:36

Learn to Design Computer Programs with Peter Norvig!

The key to progressing from a novice programmer to an expert is mindful practice. In this ...

Learn to Design Computer Programs with Peter Norvig!

The key to progressing from a novice programmer to an expert is mindful practice. In this class you will practice going from a problem description to a solution, using a series of assignments. With each problem you will learn new concepts, patterns, and methods that will expand your ability and help move you along the path from novice towards expertise.
http://www.udacity.com/overview/Course/cs212

2:29

Peter Norvig: Utility in AI

"One of our challenges for the future is to describe to our markets and to our high-tech p...

Peter Norvig: Utility in AI

"One of our challenges for the future is to describe to our markets and to our high-tech products what is it that we really want. In AI, there's a common goal of maximizing expected utility. We've spent decades on the 'expected' and the 'maximizing' parts, but have taken the 'utility' as a given. Until the public has the power to say what it is it really wants, the markets will choose poorly." - Peter Norvig, Director of Research, Google (2016)
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14:46

Peter Norvig, Google - Stanford Big Data 2015

Bringing together thought leaders in large-scale data analysis and technology to transform...

Google's Peter Norvig State of the Art AI: Building Tomorrow’s Intelligent Systems

May 23, 2016 Peter Norvig, Director of Research for Google, on developing state-of-the-art AI solutions for building tomorrow's intelligent systems.
May 23, 2016 Peter Norvig, Director of Research for Google, on developing state-of-the-art AI solutions for building tomorrow's intelligent systems. Silicon Valley .

Information and subscription on http://www.usievents.com
Director of Research at Google Inc., Peter Norvig is a reference in terms of Machine Learning. He’s always looking at the world to re-build it, playing with programs and applications that nowadays have a dominant role in our world. “The world is made of lines” and we can draw anything with it, manually or numerically.
Peter Norvig’s talk is about Deploying machine learning applications in the Enterprise.
More companies are taking advantage of the opportunity to harness large amounts of data to make more accurate predictions, and sometimes to invent entire new classes of applications that couldn't be done before. In this talk, Peter Norvig uses the exemple of Google’s photo reconnaissance or its Automatic spell-checker. “21 lines of code can now be enough to build a whole program which self-feeds”.
But like any engineering discipline, machine learning brings with it some potential pitfalls that practitioners must learn to avoid.
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7:43

You Can Always Get What You Want — But Not What You Need (Graduation 2016)

Peter Norvig - Deep Learning and Artificial Intelligence Symposium

May 1, 2017 - In less than a decade, the field of “artificial intelligence” or “AI” has been jolted by the extraordinary and unexpected success of a set of techniques now called “Deep Learning”. These methods (with some other related rapidly advancing technologies) already exceed average human performance in some kinds of image understanding; spoken word recognition and language translation; and indeed some tasks, like the game of Go, previously thought to require generalized human intelligence. AI may soon replace humans in driving cars, coding new software, robotic caregiving, and making healthcare decisions. The societal implications are enormous.
Peter Norvig, Director of Research, Google Inc. presents "Rethinking the Software Industry"

There, she was able to pitch her start-up Niramai Health Analytix and receive mentoring from the likes of Eric Schmidt, former executive chairman of Google’s parent company Alphabet, Internet pioneerVint Cerf and PeterNorvig, Google’s director of research and an expert in artificial intelligence. Dr ... Google said it was scaling up focus on women-led start-ups to include more female founders for the programme ... Ms ... ....

In addition to the three new focuses courses of study, Udacity is also revamping its core AI Nanodegree to focus on a core curriculum taught by Sebastian Thrun and PeterNorvig... This was build in partnership with Nvidia, too, as well as with Unity ... ....

Program Chairs Ben Lorica (O’Reilly), Naveen Rao (Intel) and Roger Chen (Computable Labs), along with honorary co-chairs Tim O’Reilly (O’Reilly) and PeterNorvig (Google), have created a conference program that covers emerging AI techniques and technologies with a focus on real-world implementations....

Geoffrey Hinton: The Godfather of Deep Learning

When Geoffrey Hinton, a researcher at Google and professor emeritus at the University of Toronto, began his work in deep learning in the 1970s, he was told he would spend his life toiling away in obscurity. Deep learning is a form of artificial intelligence that mimics the human brain. Now, four decades later, his research is revolutionizing AI. He joins The Agenda to discuss his work and what kept him going.

9:10

Interview with Danish hooligan (Denmark-Sweden)

A nine minutes long interview in Danish with the hooligan that ran onto the lane and hit t...

Launchpad Studio with Malika Cantor and Peter Norvig: GCPPodcast 108

Original post: https://www.gcppodcast.com/post/episode-108-lauchpad-studio-with-malika-cantor-and-peter-norvig/
LaunchpadStudio, a product development acceleration program focused on helping machine learning startups iterate quickly, fail fast, and collaborate on best practices. Malika Cantor and Peter Norvig talk with Mark and Melanie this week about how the Launchpad Studio program is helping startups overcome data, expertise and tooling barriers by providing access to talent and resources and building universal best practices.

There, she was able to pitch her start-up Niramai Health Analytix and receive mentoring from the likes of Eric Schmidt, former executive chairman of Google’s parent company Alphabet, Internet pioneerVint Cerf and PeterNorvig, Google’s director of research and an expert in artificial intelligence. Dr ... Google said it was scaling up focus on women-led start-ups to include more female founders for the programme ... Ms ... ....

In addition to the three new focuses courses of study, Udacity is also revamping its core AI Nanodegree to focus on a core curriculum taught by Sebastian Thrun and PeterNorvig... This was build in partnership with Nvidia, too, as well as with Unity ... ....

Program Chairs Ben Lorica (O’Reilly), Naveen Rao (Intel) and Roger Chen (Computable Labs), along with honorary co-chairs Tim O’Reilly (O’Reilly) and PeterNorvig (Google), have created a conference program that covers emerging AI techniques and technologies with a focus on real-world implementations....

As a general rule, the most successful man in life is the man who has the best information. aheadoftheherd.com ... It’s all good news for gold which thrives on the spectre of high government debt leading to more money-printing (aka the Federal Reserve buying Treasuries) and inflation. &nbsp; ... ... For example during NAFTA negotiations last fall, currency strategist JensNorvig was asked what would happen should NAFTA fall apart ... ***....

Artificial intelligence has been the catchphrase in recent times, but did you know that it has been written about for years now? These books will help you get started on understanding the concept’s past and future relevance. About 500 million years ago there were no traces of any living organisms on earth ... Check out the whole thread here ... Case Studies in Common Lisp by PeterNorvig ... A ModernApproach by Peter Norvig and Stuart.J.Russell....

In 1943, at the height of World War II, the U.S. military hired an audacious psychologist named B.F. Skinner to develop pigeon-guided missiles. These were the early days of munitions guidance technology, and the Allies were apparently quite desperate to find more reliable ways to get missiles to hit their targets. It went like this ...Image source ... Medium ... Size ... (Articulated by computer scientists Stuart Russell and PeterNorvig, the think vs....

Naveen Rao . &nbsp;. To get a sense of computer scientist Naveen Rao, just take a look at his hands. The 42-year-old has busted all 10 of his fingers over a lifetime of skiing, skateboarding, bicycling, rollerblading, race-car driving, wrestling and hoops ...That's some stamp of approval ... "We can now solve problems that we couldn't solve before," said PeterNorvig, director of research at Google and a key figure in the history of AI ... ....

Today's leading minds talk AI with host ByronReese. In this episode, Byron and James talk about jobs, human vs. artificial intelligence, and more. -. -. 0.00. 0.00. 0.00. Voices in AI. Visit VoicesInAI.com to access the podcast, or subscribe now. iTunes Play... But we know how to get a rocket to the moon, and gradually and slowly, little by little—No, it was PeterNorvig, who wrote the sort of standard text on artificial intelligence, called AI....

SAN DIEGO — To get a sense of computer scientist Naveen Rao, just take a look at his hands. The 42-year-old has busted all 10 of his fingers over a lifetime of skiing, skateboarding, bicycling, rollerblading, race-car driving, wrestling and hoops ... Advertisement ... “We can now solve problems that we couldn’t solve before,” said PeterNorvig, director of research at Google and a key figure in the history of AI ... ....

Helpful perks to creators to be made available at the Developers LaunchpadStudio include product validation support and introductions to AI investors, as well as feedback and advice from people like Google director of research PeterNorvig and Yossi Matias, head ......

Musk, a longtime advocate of AI, has expressed serious concerns over the years about the potential for the technology to accelerate faster than society can learn to manage its growth ...RobotApocalypse? ... . I just, I don't understand it," he said ... Other major figures, ranging from Google's PeterNorvig to Stephen Hawking and Bill Gates, in 2015 signed a letter urging more study of AI's potential impact on society ... Mirror Mirror ... ... ....